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Robust Sensor Networks: Applying AI for Fault Identification in Challenging Operational Contexts 5

Robust Sensor Networks: Applying AI for Fault Identification...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Manjunatha, A.S. Venkatramana Bhat, P. Ramakrishna, M. Prabhu, Matti Nidhi Dept. of Computer and Communication Engineering NMAM Institute of Technology Nitte Karnataka Mangaluru India Dept. of Computer Science and Engineering NMAM Institute of Technology Nitte Karnataka Mangaluru India Manipal Academy of Higher Education Dept. of Data Science and Computer Applications Manipal Institute of Technology Manipal576104 India

ISBN: (纸本)9798331518097

Wireless Sensor Networks (WSNs) are highly implemented in harsh and dynamic environments. In such configurations, faults and anomalies easily occur, causing unwanted disruptions in data accuracy and network performance. In the context of reliability and stability in WSN operations, effective fault detection techniques are vital. This research work discusses how several machine learning models may be applied, including Logistic Regression, Decision Tree, Random Forest, and K-Nearest Neighbors in order to detect fault in WSNs. The performance evaluation was performed based on major criteria, which are accuracy, precision, recall, and Fl score. This, therefore, makes these approaches to machine learning effective in identifying faults efficiently, hence offering a well-balanced solution that is scalable and robust for integrity and operational effectiveness of WSN s. © 2024 IEEE.

关键词： Random forests

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TCCL: Discovering Better Communication Paths for PCIe GPU Clusters 24

TCCL: Discovering Better Communication Paths for PCIe GPU Cl...

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29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2024

作者： Kim, Heehoon Ryu, Junyeol Lee, Jaejin Dept. of Computer Science and Engineering Seoul National University Seoul Korea Republic of Dept. of Data Science Dept. of Computer Science and Engineering Seoul National University Seoul Korea Republic of

ISBN: (纸本)9798400703867

Exploiting parallelism to train deep learning models requires GPUs to cooperate through collective communication primitives. While systems like DGX, equipped with proprietary interconnects, have been extensively studied, the systems where GPUs mainly communicate through PCIe have received limited attention. This paper introduces TCCL, a collective communication library designed explicitly for such systems. TCCL has three components: a profiler for multitransfer performance measurement, a pathfinder to discover optimal communication paths, and a modified runtime of NCCL to utilize the identified paths. The focus is on ring-based collective communication algorithms that apply to popular communication operations in deep learning, such as AllReduce and AllGather. The evaluation results of TCCL on three different PCIe-dependent GPU clusters show that TCCL outperforms (up to ×2.07) the state-of-the-art communication libraries, NCCL and MSCCL. We also evaluate TCCL with DL training workloads with various combinations of parallelism types. © 2024 Copyright held by the owner/author(s).

关键词： Graphics processing unit

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A Review Paper on Various Energy Saving Techniques in WSN

A Review Paper on Various Energy Saving Techniques in WSN

引用

2022 International Conference on Electronics and Renewable Systems, ICEARS 2022

作者： Josephine V. L., Helen Rajan, Dhivya Rajalakshmi, K. Cmr Institute of Technology Dept. of Computer Applications Karanataka Bengaluru India Montfort College Dept. Of. Computer Science Karanataka Bengaluru India

ISBN: (纸本)9781665484251

WSN (Wireless Sensor Network) is a unique variety of temporary type of Local area networks that are highly distributed self-organized systems. There is a detailed collection of various sensor nodes which are vastly deployed throughout the environment. Sensor node is a very small electronic device that is attached to a sensor network. They have an uncomplicated working mechanism that collects the data from any physical movement of an event that occurs or event query that is time driven. The notable feature of the sensor network is data gathering. Each sensory node can gather data, analyse that information and make that information to move to the location that is a destination. Routing algorithms play a vital role in making routing decision that delivers the packet to the exact point through optimal route. Since there is an energy restriction in WSNs, the energy related economisation becomes the most avoidable objective of various routing protocols. routing protocols of various sensor networks is reviewed and presented in this paper which provides a clear classification of various categories and comparison of the various methods. © 2022 IEEE.

关键词： Energy efficiency

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I. Predicting future citation counts using machine learning 22

I. Predicting future citation counts using machine learning

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22nd International Arab Conference on Information Technology, ACIT 2021

作者： Mansour, Khalid Al-Daoud, Essam Al-Karaky, Baha Data Science and AI Dept. Zarqa University Zarqa Jordan Computer Science Dept. Zarqa University Zarqa Jordan

ISBN: (纸本)9781665419956

The number of citations for a research paper is an important criterion in the scientific research community and is also an important quality indicator for both the author and the affiliated institution. Since the number of researchers, universities and scientific institutes are increasing, the number of submitted papers to scientific journals increased substantially. Consequently, the time needed to process the submitted papers is increased as well. This results in delaying publishing high quality papers. This paper proposes an approach to predict the future citations of submitted research papers using machine learning algorithms to speed up the processing time of the predicted high quality submitted papers. A dataset solicited from the International Arab Journal of Information Technology (IAJIT) is used in our experiments. The dataset covers the last ten years. Sixteen machine learning algorithms are trained on the dataset. Two sets of results are produced. The first one is related to the relative importance of features used in the prediction process. The second set shows the results of the sixteen machine learning algorithms used to predict future citations of submitted papers. The experimental results show that the number of references is the most important feature while the number of authors shown on papers is the least important feature. In addition, the results produced by neural network and voting classifier 1 techniques are slightly better than other techniques in predicting future citations. Naïve base comes next. The rest of the used machine learning methods show similar performance. © 2021 IEEE.

关键词： Forecasting

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Smart and Secure Certificate Validation System through Blockchain 2

Smart and Secure Certificate Validation System through Block...

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2nd International Conference on Inventive Research in Computing applications, ICIRCA 2020

作者： Gundgurti, Padmavati E Alluri, Kranthi Gundgurti, Poornima E Sai Harika, K. Vaishnavi, G. BVRIT HYDERABAD College of Engineering for Women Dept. of Computer Science and Engineering Hyderabad Telangana India Sharanabasaveshwara University Dept. of Computer Science and Applications Kalaburagi Karnataka India

ISBN: (纸本)9781728153742

In this paper, the problems that arise due to counterfeiting the Certificates and a platform to overcome the mentioned problem are stated. To implement the platform the concept of Blockchain isused. An incontestable advantage of Blockchain is it will make the platform decentralized. The platform is designed to store the Certificates in the block and generate a hash on the request of the student. Once the Certificates are stored in the block they become impossible to fix or to modify by anybody. Putting the information in the block will also remove doubt about the knowledge of the employee. An overview of our platform and its functionalities is presented. © 2020 IEEE.

关键词： Blockchain

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PoI: Proof of Identity and PoDI: Proof of data Integrity for Secure data Deduplication in the Cloud 2

PoI: Proof of Identity and PoDI: Proof of Data Integrity for...

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2nd International Conference on Advances in Computing, Communication, Embedded and Secure Systems, ACCESS 2021

作者： Ebinazer, Silambarasan Elkana Savarimuthu, Nickolas Bhanu, Mary Saira S. Dept. of Computer Applications National Institute of Technology Tiruchirappalli India Dept. of Computer Science and Engg. National Institute of Technology Tiruchirappalli India

ISBN: (纸本)9781728171364

Cloud storage is the decisive service for the organization, hospitals etc., for storing huge amount of data within their budget. But, Cloud Service Providers (CSPs) are facing the major problem of duplicate and redundant data being accumulated by data Owners (DO) in the cloud storages. Deduplication is one of the major technique to solve the above problem but faces the major drawback in the form of security flaws. Secure deduplication is a very promising solution proposed by the researchers for addressing this issue. In this paper, problems like revocation of DOs, brute force attack and duplicate faking attack are addressed as part of secure deduplication. The proposed approach is having two protocols, namely, Proof of Identity (PoI) and Proof of data Integrity (PoDI) which solves the above-mentioned problems. The proposed approach improves the efficiency of secure deduplication, enhances data privacy and addresses data Owner (DO) revocation problem. © 2021 IEEE

关键词： Cloud storage

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SRSnF: A strategy for secured routing in spray and focus routing protocol for DTN

SRSnF: A strategy for secured routing in spray and focus rou...

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2nd International Conference on Advances in Computing and Information Technology, ACITY-2012

作者： Saha, Sujoy Verma, Rohit Sengupta, Satadal Mishra, Vineet Nandi, Subrata Dept. of Computer Science and Engineering National Institute of Technology Durgapur India Dept. of Computer Applications National Institute of Technology Durgapur 713209 India

ISBN: (纸本)9783642315121

This paper deals with the aspect of security in Delay Tolerant Networks (DTN). DTNs are characterized with decentralized control. Network performance and trustworthiness of transmitted information in DTNs depend upon the level of co-operation among participating nodes. As a result, DTNs are vulnerable towards untoward activities arising out of node selfishness as well as malicious intentions. In this paper, we limit our focus to the Black Hole Denial-of-Service attack. We develop a table-based strategy to record network history and use this information to detect discrepancies in the behavior of nodes, followed by elimination of those detected as malicious. We explain our detection mechanism considering Spray & Focus routing protocol as the representative routing scheme. The detection mechanism has been described in detail with examples pertaining to various case scenarios. Furthermore, we study the effect of variation of various parameters on detection efficiency and message transmission through simulation results. © 2012 Springer-Verlag.

关键词： Delay tolerant networks

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Predictive Analysis of Diabetes Mellitus Using Decision Tree Approach 2

Predictive Analysis of Diabetes Mellitus Using Decision Tree...

引用

2nd Asian Conference on Innovation in Technology, ASIANCON 2022

作者： Thotad, Puneeth Bharamagoudar, Geeta R. Anami, Basavaraj S. Kle Institute of Technology Dept. of Master of Computer Applications Hubballi India Kle Institute of Technology Dept. of Computer Science & Engineering Hubballi India

ISBN: (数字)9781665468510

ISBN: (纸本)9781665468510

Diabetes Mellitus is one of the Non-Communicable Disease. It is characterized by hyperglycemia. It may be reason for numerous health difficulties. According to the statistics in coming years, in 2030, worldwide it reaches up to 643 million counts of diabetic patients. The various factors such as Bad Diet, High Blood Pressure, Obesity, Age, Lack of Exercise etc. can led to Diabetes Mellitus. The various diseases like nerve damage, heart problem, eye problem, kidney disease, stroke in many people caused by high risk of Diabetes Mellitus. Machine Learning plays vital role in healthcare sectors. Using various Machine Learning techniques, a study can be done on large datasets and discover unseen facts, unseen patterns to realize awareness from the data and predict results consequently. In this work, the PIMA Indian Diabetes dataset is considered for Predictive Analysis. The Decision Tree algorithm, namely ID3 (Iterative Dichotomize 3) is used for a predictive analysis. The major phases include preprocessing, feature extraction, classification, and prediction. The classification accuracies of 79.76% and 76.3% are obtained for balanced and unbalanced datasets respectively. The maximum specificity and sensitivity obtained are 79.75% and 79.78% respectively. The ROC curve gives 79.57% overall classification accuracy. The work assists physicians as a second opinion. It can help various health industries to predict the diabetes disease in a better way. © 2022 IEEE.

关键词： Decision trees

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Automatic Segmentation based Graphical Interface for Recognition of Tomography Image Analysis of Damage cell 3

Automatic Segmentation based Graphical Interface for Recogni...

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3rd International Conference on Inventive Systems and Control, ICISC 2019

作者： Rao, K Rajesh Samanta, Debabrata Somashekara, M.T. Gurunath, R. Paul, Abhishek Acharya Institute of Institute Department of MCA Bangalore India DayanandaSagar College of Arts Science and Commerce Dept. of Computer Applications Bangalore India Bangalore University Dept. of Computer Applications Bangalore India

ISBN: (纸本)9781538639504

The recent improvement in Medical picture development has facilitated Computed Tomography Image study by Automatic division of impaired cell. Automatic division of impaired cell will provide the required information, cross correlation and log value. The contrast between ordinary and impaired cell will provide a correct notion about the impaired cell. Employing the GUI technique, the operator can distinct the provided two image characteristics and accomplish the appropriate examination of the medical image. The benefits of this suggested technique are inexpensive, less time consuming and simple to operate. The operator can easily insert and speculate the values. © 2019 IEEE.

关键词： Cells

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Hindi News Article's Headline Generation based on Abstractive Text Summarization

Hindi News Article's Headline Generation based on Abstractiv...

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2023 IEEE International Conference on Network, Multimedia and Information Technology, NMITCON 2023

作者： Kumar, Jeetendra Shekhar, Shashi Gupta, Rashmi Atal Bihari Vajpayee University Dept. of Computer Science and Application Bilaspur India Gla University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798350300826

Text summarization is a technique that converts large text into shorter ones by keeping its important information. Most of the available summarizers, summarize English language text. The availability of summarizers in other languages is rare. In the proposed work, abstractive text summarization (ATS) for the Hindi language has been used to generate headlines from news text. To build the model, a Hindi news dataset has been used that contains different news articles related to sports, politics, crime, etc. After pre-processing the text, Word2Vec method has been used for word embedding. ATS model has been built using the Seq2Seq model with attention. After that, we have calculated evaluation metrics like ROUGE and BLEU scores of the result summaries. We have also fine-tuned two pre-trained models, indicBART and multi-lingual variant of T5. After result comparison, it was found that the indicBART perform better than the other two models, considered for the experiment. © 2023 IEEE.

关键词： Text processing

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